Hierarchical Data Integrity for IoT Devices in Connected Health Applications

Internet of things devices are increasingly replacing expensive monitoring devices in many environments such as healthcare. People can eventually own their data, collected from smart personal devices, store them in a variety of cloud services, and make them available to service providers of their choice. In such cases, whenever service providers use these data to provide appropriate services, the data owner may become responsible for ensuring the integrity of data retrieved from multiple points. We present a Hierarchical Data Integrity (HDI) approach to verify if the data, sent by monitoring devices to the cloud, remain unchanged. It is hierarchical as follows: there is a quick verification of the integrity of recent health data (in less than 1 ms), followed if necessary by a low overhead secure option for verifying the integrity of both recent and historical data (still only in 6:1 ms). Further, the hierarchy allows granular identification of data units that fail integrity checks, without requiring any key sharing. It is possible for a data owner to periodically (randomly) use a more secure process to verify the integrity of data. This reduces the computation, storage, and time of integrity verification as shown by analysis, simulation, and hardware implementation

Efficient, Dependable Storage of Human Genome Sequencing Data

A compreensão do genoma humano impacta várias áreas da vida. Os dados oriundos do genoma humano são enormes pois existem milhões de amostras a espera de serem sequenciadas e cada genoma humano sequenciado pode ocupar centenas de gigabytes de espaço de armazenamento. Os genomas humanos são críticos porque são extremamente valiosos para a investigação e porque podem fornecer informações delicadas sobre o estado de saúde dos indivíduos, identificar os seus dadores ou até mesmo revelar informações sobre os parentes destes. O tamanho e a criticidade destes genomas, para além da quantidade de dados produzidos por instituições médicas e de ciências da vida, exigem que os sistemas informáticos sejam escaláveis, ao mesmo tempo que sejam seguros, confiáveis, auditáveis e com custos acessíveis. As infraestruturas de armazenamento existentes são tão caras que não nos permitem ignorar a eficiência de custos no armazenamento de genomas humanos, assim como em geral estas não possuem o conhecimento e os mecanismos adequados para proteger a privacidade dos dadores de amostras biológicas. Esta tese propõe um sistema de armazenamento de genomas humanos eficiente, seguro e auditável para instituições médicas e de ciências da vida. Ele aprimora os ecossistemas de armazenamento tradicionais com técnicas de privacidade, redução do tamanho dos dados e auditabilidade a fim de permitir o uso eficiente e confiável de infraestruturas públicas de computação em nuvem para armazenar genomas humanos. As contribuições desta tese incluem (1) um estudo sobre a sensibilidade à privacidade dos genomas humanos; (2) um método para detetar sistematicamente as porções dos genomas que são sensíveis à privacidade; (3) algoritmos de redução do tamanho de dados, especializados para dados de genomas sequenciados; (4) um esquema de auditoria independente para armazenamento disperso e seguro de dados; e (5) um fluxo de armazenamento completo que obtém garantias razoáveis de proteção, segurança e confiabilidade a custos modestos (por exemplo, menos de $1/Genoma/Ano), integrando os mecanismos propostos a configurações de armazenamento apropriadasThe understanding of human genome impacts several areas of human life. Data from human genomes is massive because there are millions of samples to be sequenced, and each sequenced human genome may size hundreds of gigabytes. Human genomes are critical because they are extremely valuable to research and may provide hints on individuals’ health status, identify their donors, or reveal information about donors’ relatives. Their size and criticality, plus the amount of data being produced by medical and life-sciences institutions, require systems to scale while being secure, dependable, auditable, and affordable. Current storage infrastructures are too expensive to ignore cost efficiency in storing human genomes, and they lack the proper knowledge and mechanisms to protect the privacy of sample donors. This thesis proposes an efficient storage system for human genomes that medical and lifesciences institutions may trust and afford. It enhances traditional storage ecosystems with privacy-aware, data-reduction, and auditability techniques to enable the efficient, dependable use of multi-tenant infrastructures to store human genomes. Contributions from this thesis include (1) a study on the privacy-sensitivity of human genomes; (2) to detect genomes’ privacy-sensitive portions systematically; (3) specialised data reduction algorithms for sequencing data; (4) an independent auditability scheme for secure dispersed storage; and (5) a complete storage pipeline that obtains reasonable privacy protection, security, and dependability guarantees at modest costs (e.g., less than$1/Genome/Year) by integrating the proposed mechanisms with appropriate storage configurations

Computer Science & Technology Series : XVI Argentine Congress of Computer Science - Selected papers

CACIC’10 was the sixteenth Congress in the CACIC series. It was organized by the School of Computer Science of the University of Moron. The Congress included 10 Workshops with 104 accepted papers, 1 main Conference, 4 invited tutorials, different meetings related with Computer Science Education (Professors, PhD students, Curricula) and an International School with 5 courses. (http://www.cacic2010.edu.ar/). CACIC 2010 was organized following the traditional Congress format, with 10 Workshops covering a diversity of dimensions of Computer Science Research. Each topic was supervised by a committee of three chairs of different Universities. The call for papers attracted a total of 195 submissions. An average of 2.6 review reports were collected for each paper, for a grand total of 507 review reports that involved about 300 different reviewers. A total of 104 full papers were accepted and 20 of them were selected for this book.Red de Universidades con Carreras en Informática (RedUNCI

Personalization in Recommender Systems through Explainable Machine Learning

[Abstract]: Recommender Systems have become ubiquitously utilized tools in multiple fields such as media streaming services, travelling and tourism business, e-commerce, and numerous others. However, in practice they show a tendency to be black-box systems, despite their increasing influence in people’s daily lives. There is a lack of research on providing personalised explanations to the recommendations of a system, that is, integrating the idea of Explainable Artificial Intelligence into the field of Recommender Systems. Therefore, we do not seek to create a Recommender System, but instead devise a way to obtain this explainability or personalisation in such type of tool. In this work, we propose a model able to provide said personalisation by generating explanations based on user-created content, namely text or photographs. In the context of the restaurant review platform TripAdvisor, we will predict, for any (user,restaurant) pair or existing recommendation, the text or image of the restaurant that is most adequate to present said recommendation to the user, that is, the one that best reflects their personal preferences. This model exploits the usage of Matrix Factorisation techniques combined with the feature-rich embeddings of pre-trained image classification and language models (Inception-ResNet-v2 and BERT), to develop a method capable of providing transparency to Recommender Systems.[Resumen]: Los Sistemas de Recomendación se han convertido en herramientas usadas extensivamente en multitud de campos como online streaming, turismo, restauración, viajes y comercio electrónico, así como muchos otros. Sin embargo, en la práctica presentan una tendencia a ser sistemas de caja negra, pese a la cada vez mayor influencia que presentan sobre el día a día de nuestra sociedad. Hay una falta de investigación sobre la idea de aportar explicaciones personalizadas a las recomendaciones de un sistema, es decir, integrar el concepto de Inteligencia Artifical Explicable en el área de los Sistemas de Recomendación. Por lo tanto, no buscamos crear un Sistema de Recomendación per se, sino idear un modo de obtener esta capacidad de explicabilidad o personalización en dicho tipo de sistemas. En este trabajo, proponemos un modelo capaz de proveer de esta personalización mediante la generación de explicaciones basadas en contenido generado por los usuarios, en particular texto e imágenes. En el contexto de la plataforma de reseñas de restaurantes TripAdvisor, buscaremos predecir, para cualquier par o posible recomendación (usuario, restaurante), la imagen o texto sobre dicho restaurante más adecuada para presentar esa recomendación al usuario, es decir, la imagen o texto que mejor refleja las preferencias personales del usuario. Este modelo explota el uso de técnicas de Factorización Matricial combinadas con modelos de lenguaje y clasificación de imágenes (BERT e Inception-ResNet-v2), para desarrollar un método con capacidad de otorgar transparencia a Sistemas de Recomendación.Traballo fin de grao (UDC.FIC). Enxeñaría Informática. Curso 2020/202

Classes-Chave em sistemas orientados a objetos: detecção e uso

Several object-oriented systems, such as Lucene, Tomcat, Javac have their respective design documented using key-classes, defined as important/central classes to understand the object-oriented design. Considering this fact, and considering that, in general, software architecture is not formally documented to help developers understanding and assessing software design, Keecle is proposed as an approach based on dynamic and static analysis for detection of key classes in a semi-automatic way. The application of filtering mechanisms on the search space of the dynamic data is proposed in order to obtain a reduced set of key classes. The approach is evaluated with fourteen proprietary and open source systems in order to verify that the found classes correspond to the key classes of the ground-truth, which is defined from the documentation or defined by the developers. The results were analyzed in terms of precision and recall, and have shown to be superior to the state-of-the-art approach. The role of key classes in assessing design has also been investigated. The organization of the key classes in a dependency graph, which highlights explicit dependency relations in the source code, was evaluated to be adequate for design comprehension and assessment. Key classes were evaluated whether they are more prone to bad smells, and whether specific types of bad smells are associated with different levels of cohesion and coupling metrics. In addition, the ownership of key classes was shown to be more concentrated in a reduced set of developers. Finally, we conducted an experimental study with students and a survey with developers to evaluate documentation based on key classes. The results indicate that the documentation based on key classes are a feasible alternative for use as complementary documentation to the existing one, or for use as main documentation in environments where documentation is not available.FAPEG - Fundação de Amparo à Pesquisa do Estado de GoiásTese (Doutorado)Vários sistemas orientados a objetos, tais como Lucene, Tomcat, Javac tem seus respectivos projetos (designs) documentados usando classes-chave, definidas como sendo classes importantes/centrais para compreender o projeto de sistemas orientados a objetos. Considerando este fato, e considerando que geralmente a arquitetura não é formalmente documentada para auxiliar os desenvolvedores a entenderem e avaliarem o projeto do software, é proposta Keecle, uma abordagem baseada em análise dinâmica e estática para detecção de classes-chave de maneira semi-automática. É proposta a aplicação de mecanismos de filtragem no espaço de busca dos dados dinâmicos, para obter um conjunto reduzido de classes-chave. A abordagem é avaliada com quatorze sistemas de código aberto e proprietários, a fim de verificar se as classes encontradas correspondem às classes-chave definidas na documentação ou definidas pelos desenvolvedores. Os resultados foram analisados em termos de precisão e recall e são superiores às abordagens da literatura. O papel das classes-chave para avaliar o projeto também foi investigado. Foi avaliado se a organização das classes-chave em um grafo de dependências, o qual destaca relações de dependência explícitas no código fonte, é um mecanismo adequado para avaliar o design. Foi analisado estatisticamente, se classes-chave são mais propensas a bad smells, e se tipos específicos de bad smells estão associados a diferentes níveis de métricas de coesão e acoplamento. Além disso, a propriedade (ownership) das classes-chave foi analisada, indicando concentração em um conjunto reduzido de desenvolvedores. Por fim, foram conduzidos um estudo experimental com estudantes e um survey com desenvolvedores para avaliar a documentação baseada em classes-chave. Os resultados demonstram que a documentação baseada em classes-chave apresenta resultados que indicam a viabilidade de uso como documentação complementar à existente ou como documentação principal em ambientes onde a documentação não está disponível

Appreciative merger and acquisition team coaching programme to facilitate managers' mental health in a cross-cultural context

D.Cur.(Psychiatric Nursing Science)One overarching research aim guided me in this research, namely to generate a worthy Appreciative Merger & Acquisition (M&A) team coaching programme to facilitate managers’ mental health in the context of a cross-cultural M&A. The context represented a hotel in Swaziland, which was situated in a Southern African hospitality environment. A variety of stories reflecting the paradoxical, alienating nature of M&As impelled me to enter the research context. At the same time, research and literature confirmed a preference for organisational change strategies that depart from a deficit orientation. These change strategies presuppose that something is broken in the organisational context, which needs to be repaired. Inherent power-driven organisational change processes are often employed as a strategy to try and repair the identified organisational brokenness. It was, therefore, from a position of curiosity regarding the cross-cultural M&A experiences of managers in the particular hospitality environment, as well as interest in positive organisational change initiatives, that I have gone on this journey. Positive organisational change initiatives celebrate the life-giving stories of organisational life. It departs from the assumption that something in an organisation does work. On entry, I hoped that the context would lend itself to implementing an existing M&A team coaching programme. Additionally, that the stakeholders involved would allow the transfer of such a programme in order to establish its worth while contributing to the advancement of theory in the field of business coaching. Two central research questions were asked. These questions related to the existence of an M&A team coaching programme that lacked scientific credibility at the time, as well as literature that confirmed the detrimental influence of mismanaged cross-cultural M&A implementation processes driven from a deficit orientation on the mental health of managers. • Can an M&A team coaching programme to facilitate managers’ mental health for sustained performance be applied to a cross-cultural M&A in a Southern African hospitality environment? • If the programme is applicable, how can it be refined, implemented and valuated as a foundation to generate a worthy Appreciative M&A team coaching programme to facilitate managers’ mental health for sustained performance in a Southern African hospitality environment